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To take the DP-203 exam, you should have a solid understanding of data processing technologies, data storage options, data security and compliance, and data integration and transformation techniques. You should also be familiar with Azure services such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Stream Analytics. By passing DP-203 exam, you can prove your ability to work with Azure tools and technologies, and showcase your expertise in data engineering on the Microsoft Azure platform.

The Data Engineering on Microsoft Azure certification exam is an excellent choice for professionals who want to demonstrate their expertise in data engineering on Azure. Data Engineering on Microsoft Azure certification is globally recognized and is highly valued by employers. DP-203 Exam is also an excellent opportunity for professionals to enhance their skills and knowledge in data engineering on Azure, allowing them to take on more challenging roles in their organizations.

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To prepare for the Microsoft DP-203 Certification Exam, you will need to have a solid understanding of Azure data services, including Azure Databricks, Azure Data Factory, Azure Stream Analytics, and Azure Cosmos DB. You will also need to be familiar with data integration and transformation techniques, as well as data security and compliance requirements. Microsoft offers a range of training resources and study materials to help you prepare for the exam, including online courses, practice exams, and virtual labs.

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q18-Q23):

NEW QUESTION # 18
You have an Azure Data Factory pipeline that has the activities shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://datasavvy.me/2021/02/18/azure-data-factory-activity-failures-and-pipeline-outcomes/

NEW QUESTION # 19
You need to output files from Azure Data Factory.
Which file format should you use for each type of output? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: Parquet
Parquet stores data in columns, while Avro stores data in a row-based format. By their very nature, column-oriented data stores are optimized for read-heavy analytical workloads, while row-based databases are best for write-heavy transactional workloads.
Box 2: Avro
An Avro schema is created using JSON format.
AVRO supports timestamps.
Note: Azure Data Factory supports the following file formats (not GZip or TXT).
* Avro format
* Binary format
* Delimited text format
* Excel format
* JSON format
* ORC format
* Parquet format
* XML format
Reference:
https://www.datanami.com/2018/05/16/big-data-file-formats-demystified

NEW QUESTION # 20
You have an Azure Active Directory (Azure AD) tenant that contains a security group named Group1. You have an Azure Synapse Analytics dedicated SQL pool named dw1 that contains a schema named schema1.
You need to grant Group1 read-only permissions to all the tables and views in schema1. The solution must use the principle of least privilege.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Answer:

Explanation:

Explanation

Step 1: Create a database role named Role1 and grant Role1 SELECT permissions to schema You need to grant Group1 read-only permissions to all the tables and views in schema1.
Place one or more database users into a database role and then assign permissions to the database role.
Step 2: Assign Rol1 to the Group database user
Step 3: Assign the Azure role-based access control (Azure RBAC) Reader role for dw1 to Group1 Reference:
https://docs.microsoft.com/en-us/azure/data-share/how-to-share-from-sql

NEW QUESTION # 21
You need to design the partitions for the product sales transactions. The solution must meet the sales transaction dataset requirements.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Box 1: Sales date
Scenario: Contoso requirements for data integration include:
Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month. Boundary values must belong to the partition on the right.
Box 2: An Azure Synapse Analytics Dedicated SQL pool
Scenario: Contoso requirements for data integration include:
Ensure that data storage costs and performance are predictable.
The size of a dedicated SQL pool (formerly SQL DW) is determined by Data Warehousing Units (DWU).
Dedicated SQL pool (formerly SQL DW) stores data in relational tables with columnar storage. This format significantly reduces the data storage costs, and improves query performance.
Synapse analytics dedicated sql pool
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-overview- what-is

NEW QUESTION # 22
A company plans to use Platform-as-a-Service (PaaS) to create the new data pipeline process. The process must meet the following requirements:
Ingest:
Access multiple data sources.
Provide the ability to orchestrate workflow.
Provide the capability to run SQL Server Integration Services packages.
Store:
Optimize storage for big data workloads.
Provide encryption of data at rest.
Operate with no size limits.
Prepare and Train:
Provide a fully-managed and interactive workspace for exploration and visualization.
Provide the ability to program in R, SQL, Python, Scala, and Java.
Provide seamless user authentication with Azure Active Directory.
Model & Serve:
Implement native columnar storage.
Support for the SQL language
Provide support for structured streaming.
You need to build the data integration pipeline.
Which technologies should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 23
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